Machine Learning for Security in Vehicular Networks: A Comprehensive Survey

Machine Learning (ML) has emerged as an attractive and viable technique to provide effective solutions for a wide range of application domains. An important domain is vehicular networks wherein ML-based approaches are found be very useful address various problems. The use wireless communication between nodes and/or infrastructure makes it vulnerable different types attacks. In this regard, ML its variants gaining popularity detect attacks deal with kinds security issues in communication. paper, we present comprehensive survey techniques networks. We first briefly introduce the basics communications. Apart from traditional networks, also consider modern network architectures. propose taxonomy discuss challenges requirements. classify developed literature according their applications. explain solution working principles these addressing insightful discussion. limitations using methods discussed. Finally, observations lessons learned before conclude our work.